Contents

Bernoulli

Blahut-Arimoto

Channel Capacity

Classification

Convolutional Neural Networks

Cost Function

Cross Entropy

Entropy

Exponential Family

Gaussian

Information Bottleneck

Information Plane

Information Theory

Kullback-Leibler Divergence

Log-loss Function

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Maximum Likelihood Estimation

Network Pruning

Optimization

Probability Distribution Functions

Rate Distortion Theory

Recurrent Neural Networks

Regression

Research Interest

Tiny ML

Turing Machines

Tutorial